Product Manager - Genius AI Platform

Product Management
· Individual Contributor Leader
· 8+ Years

Every day, Global Payments makes it possible for millions of people to move money between buyers and sellers using our payments solutions for credit, debit, prepaid and merchant services. Our worldwide team helps over 3 million companies, more than 1,300 financial institutions and over 600 million cardholders grow with confidence and achieve amazing results. We are driven by our passion for success and we are proud to deliver best-in-class payment technology and software solutions.

Join our dynamic team and make your mark on the payments technology landscape of tomorrow.

Global Payments is investing in AI across its software and payments portfolio. We’re hiring a Lead Product Manager, AI Platform to own the shared foundation that product teams across the company use to build AI experiences. You’ll set the platform strategy, make build-vs-buy decisions, and test ideas with your own working prototypes before teams commit engineering capacity.

This is a platform role. You won’t ship a single feature. You’ll build the foundation that many AI products are built on. Your direct customers are the product and engineering teams building on the platform, and your success is measured by the value they deliver to the businesses we serve.

• Define the multi-year vision and roadmap for a shared AI platform, and make it the default path for teams building AI capabilities.
• Lead build-vs-buy-vs-partner decisions for core platform components, with clear trade-offs on portability, lock-in, cost, latency and security.
• Own the model portfolio and AI unit economics, including routing rules, cost per interaction and pricing inputs to the business.
• Manage relationships with cloud and model vendors, including roadmap influence and commercial terms.

• Own the platform’s core building blocks, such as orchestration, tools, workflows, connectors and agents, and be clear about when each pattern is the right one.
• Define standards for how capabilities are exposed and integrated, including interfaces, schemas, error handling, permissions and safe handling of actions that change data.
• Own how context, memory, identity and data access work across tenants and use cases.

• Build an evaluation practice that combines offline test sets, automated and human review, production quality signals and release gates.
• Own guardrails and responsible-AI controls suited to a regulated payments environment, including data privacy, AI-specific security threats, grounding, action authorization and auditability.
• Set production targets for quality, latency, availability and cost, and own the incident and rollback playbooks.

• Build working prototypes yourself, taking a customer problem to a demoable prototype in one to two weeks without dedicated engineering support.
• Ship every prototype with a small evaluation set, a cost estimate, a latency measurement and a short note on what it would take to product ionize.
• Treat prototypes as evidence for decisions, not production systems, and keep a clear record of each problem, prototype and decision.

• Drive platform adoption across product and engineering teams, and run platform reviews with architecture, security, legal and risk.
• Explain platform direction to senior leaders in plain language, and write the documents that keep a multi-team program aligned.
• Mentor other product managers on AI product practice as an individual contributor leader.

• 8+ years of…